Senior Data Engineer

Loop Recruitment is representing an exciting, fast-growing SaaS company operating in the insurance technology space, building scalable platforms that power customer acquisition and real-time decisioning. They are seeking a Senior Data Engineer to design, build, and scale a modern data platform, focusing on creating reliable data systems and collaborating with cross-functional teams to deliver high-quality data solutions.

Responsibilities:

• Design, build, and maintain scalable ETL / ELT pipelines across batch and real-time environments
• Architect and own the OLAP data platform (Redshift and related components), partnering with product engineers on OLTP data integrations
• Build reliable, observable, and maintainable pipelines using Python, AWS Glue, Kafka / Kinesis
• Define and enforce best practices around data quality, validation, automated testing, and CI/CD
• Own and evolve data models supporting analytics, product usage tracking, and real-time decision-making
• Collaborate with BI, Product, and cross-functional stakeholders to translate requirements into robust data solutions
• Improve data reliability, governance, lineage, and observability across the stack
• Mentor engineers and help set strong data engineering and platform standards

Requirements:

• 5+ years' experience as a Data Engineer working with large-scale data systems
• Strong Python expertise for building and orchestrating data pipelines
• Deep experience with AWS Redshift, including performance tuning, modelling, and workload management
• Hands-on experience with AWS Glue, Kafka/Kinesis, and streaming data patterns
• Proven Data DevOps experience, including: Managing OLAP data infrastructure, Coordinating OLTP data workflows with product engineering, CI/CD and infrastructure tooling (Terraform, CloudFormation, GitHub Actions, CodePipeline, etc.) & Automated testing frameworks for data
• Strong communicator - comfortable partnering with BI and product teams to design scalable data solutions
• Ownership-driven mindset and comfort in a fast-paced, growth-oriented SaaS environment
• Confident using modern AI-assisted development tools (e.g. Cursor, Claude Code, agent-based tooling) - knowing when to trust, adapt, or override outputs to deliver high-quality solutions
• Experience with ClickHouse or other analytical databases
• Exposure to workflow orchestrators (Airflow, etc.)
• Docker and container platforms (ECS, EKS, etc.)
• Familiarity with data observability tooling